{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fit go/no-go using the chi-qsuare approach\n",
    "### by Jan Willem de Gee (jwdegee@gmail.com)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a demo of fitting go/no-go data with HDDM using the chi-qsuare method, as described in \n",
    "\n",
    "    de Gee JW, Tsetsos T, McCormick DA, McGinley MJ & Donner TH. 2018. Phasic arousal optimizes decision computations in mice and humans. bioRxiv. (https://www.biorxiv.org/content/early/2018/10/19/447656).\n",
    "    \n",
    "\n",
    "See also\n",
    "    \n",
    "    Ratcliff, R., Huang-Pollock, C., & McKoon, G. (2016). Modeling individual differences in the go/no-go task with a diffusion model. Decision, 5(1), 42-62 (http://psycnet.apa.org/record/2016-39470-001)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load packages\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import hddm\n",
    "from joblib import Parallel, delayed"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's start with defining some functionality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_choice(row):\n",
    "    if row.condition == \"present\":\n",
    "        if row.response == 1:\n",
    "            return 1\n",
    "        else:\n",
    "            return 0\n",
    "    elif row.condition == \"absent\":\n",
    "        if row.response == 0:\n",
    "            return 1\n",
    "        else:\n",
    "            return 0\n",
    "\n",
    "\n",
    "def simulate_data(\n",
    "    a, v, t, z, dc, sv=0, sz=0, st=0, condition=0, nr_trials1=1000, nr_trials2=1000\n",
    "):\n",
    "    \"\"\"\n",
    "    Simulates stim-coded data.\n",
    "    \"\"\"\n",
    "\n",
    "    parameters1 = {\"a\": a, \"v\": v + dc, \"t\": t, \"z\": z, \"sv\": sv, \"sz\": sz, \"st\": st}\n",
    "    parameters2 = {\n",
    "        \"a\": a,\n",
    "        \"v\": v - dc,\n",
    "        \"t\": t,\n",
    "        \"z\": 1 - z,\n",
    "        \"sv\": sv,\n",
    "        \"sz\": sz,\n",
    "        \"st\": st,\n",
    "    }\n",
    "    df_sim1, params_sim1 = hddm.generate.gen_rand_data(\n",
    "        params=parameters1, size=nr_trials1, subjs=1, subj_noise=0\n",
    "    )\n",
    "    df_sim1[\"condition\"] = \"present\"\n",
    "    df_sim2, params_sim2 = hddm.generate.gen_rand_data(\n",
    "        params=parameters2, size=nr_trials2, subjs=1, subj_noise=0\n",
    "    )\n",
    "    df_sim2[\"condition\"] = \"absent\"\n",
    "    df_sim = pd.concat((df_sim1, df_sim2))\n",
    "    df_sim[\"bias_response\"] = df_sim.apply(get_choice, 1)\n",
    "    df_sim[\"correct\"] = df_sim[\"response\"].astype(int)\n",
    "    df_sim[\"response\"] = df_sim[\"bias_response\"].astype(int)\n",
    "    df_sim[\"stimulus\"] = np.array(\n",
    "        (np.array(df_sim[\"response\"] == 1) & np.array(df_sim[\"correct\"] == 1))\n",
    "        + (np.array(df_sim[\"response\"] == 0) & np.array(df_sim[\"correct\"] == 0)),\n",
    "        dtype=int,\n",
    "    )\n",
    "    df_sim[\"condition\"] = condition\n",
    "    df_sim = df_sim.drop(columns=[\"bias_response\"])\n",
    "\n",
    "    return df_sim\n",
    "\n",
    "\n",
    "def fit_subject(data, quantiles):\n",
    "    \"\"\"\n",
    "    Simulates stim-coded data.\n",
    "    \"\"\"\n",
    "\n",
    "    subj_idx = np.unique(data[\"subj_idx\"])\n",
    "    m = hddm.HDDMStimCoding(\n",
    "        data,\n",
    "        stim_col=\"stimulus\",\n",
    "        split_param=\"v\",\n",
    "        drift_criterion=True,\n",
    "        bias=True,\n",
    "        p_outlier=0,\n",
    "        depends_on={\n",
    "            \"v\": \"condition\",\n",
    "            \"a\": \"condition\",\n",
    "            \"t\": \"condition\",\n",
    "            \"z\": \"condition\",\n",
    "            \"dc\": \"condition\",\n",
    "        },\n",
    "    )\n",
    "    m.optimize(\"gsquare\", quantiles=quantiles, n_runs=8)\n",
    "    res = pd.concat(\n",
    "        (\n",
    "            pd.DataFrame([m.values], index=[subj_idx]),\n",
    "            pd.DataFrame([m.bic_info], index=[subj_idx]),\n",
    "        ),\n",
    "        axis=1,\n",
    "    )\n",
    "    return res\n",
    "\n",
    "\n",
    "def summary_plot(\n",
    "    df_group,\n",
    "    df_sim_group=None,\n",
    "    quantiles=[\n",
    "        0,\n",
    "        0.1,\n",
    "        0.3,\n",
    "        0.5,\n",
    "        0.7,\n",
    "        0.9,\n",
    "    ],\n",
    "    xlim=None,\n",
    "):\n",
    "    \"\"\"\n",
    "    Generates a\n",
    "    \"\"\"\n",
    "\n",
    "    nr_subjects = len(np.unique(df_group[\"subj_idx\"]))\n",
    "\n",
    "    fig = plt.figure(figsize=(10, nr_subjects * 2))\n",
    "    plt_nr = 1\n",
    "    for s in np.unique(df_group[\"subj_idx\"]):\n",
    "        df = df_group.copy().loc[(df_group[\"subj_idx\"] == s), :]\n",
    "        df_sim = df_sim_group.copy().loc[(df_sim_group[\"subj_idx\"] == s), :]\n",
    "        df[\"rt_acc\"] = df[\"rt\"].copy()\n",
    "        df.loc[df[\"correct\"] == 0, \"rt_acc\"] = df.loc[df[\"correct\"] == 0, \"rt_acc\"] * -1\n",
    "        df[\"rt_resp\"] = df[\"rt\"].copy()\n",
    "        df.loc[df[\"response\"] == 0, \"rt_resp\"] = (\n",
    "            df.loc[df[\"response\"] == 0, \"rt_resp\"] * -1\n",
    "        )\n",
    "        df_sim[\"rt_acc\"] = df_sim[\"rt\"].copy()\n",
    "        df_sim.loc[df_sim[\"correct\"] == 0, \"rt_acc\"] = (\n",
    "            df_sim.loc[df_sim[\"correct\"] == 0, \"rt_acc\"] * -1\n",
    "        )\n",
    "        df_sim[\"rt_resp\"] = df_sim[\"rt\"].copy()\n",
    "        df_sim.loc[df_sim[\"response\"] == 0, \"rt_resp\"] = (\n",
    "            df_sim.loc[df_sim[\"response\"] == 0, \"rt_resp\"] * -1\n",
    "        )\n",
    "        max_rt = np.percentile(df_sim.loc[~np.isnan(df_sim[\"rt\"]), \"rt\"], 99)\n",
    "        bins = np.linspace(-max_rt, max_rt, 30)\n",
    "        # rt distributions correct vs error:\n",
    "        ax = fig.add_subplot(nr_subjects, 4, plt_nr)\n",
    "        N, bins, patches = ax.hist(\n",
    "            df.loc[:, \"rt_acc\"], bins=bins, density=True, color=\"green\", alpha=0.5\n",
    "        )\n",
    "\n",
    "        for bin_size, bin, patch in zip(N, bins, patches):\n",
    "            if bin < 0:\n",
    "                plt.setp(patch, \"facecolor\", \"r\")\n",
    "        if df_sim is not None:\n",
    "            ax.hist(\n",
    "                df_sim.loc[:, \"rt_acc\"],\n",
    "                bins=bins,\n",
    "                density=True,\n",
    "                histtype=\"step\",\n",
    "                color=\"k\",\n",
    "                alpha=1,\n",
    "                label=None,\n",
    "            )\n",
    "        ax.set_title(\n",
    "            \"P(correct)={}\".format(\n",
    "                round(df.loc[:, \"correct\"].mean(), 3),\n",
    "            )\n",
    "        )\n",
    "        ax.set_xlabel(\"RT (s)\")\n",
    "        ax.set_ylabel(\"Trials (prob. dens.)\")\n",
    "        plt_nr += 1\n",
    "\n",
    "        # condition accuracy plots:\n",
    "        ax = fig.add_subplot(nr_subjects, 4, plt_nr)\n",
    "        df.loc[:, \"rt_bin\"] = pd.qcut(df[\"rt\"], quantiles, labels=False)\n",
    "        d = df.groupby([\"rt_bin\"]).mean().reset_index()\n",
    "        ax.errorbar(\n",
    "            d.loc[:, \"rt\"], d.loc[:, \"correct\"], fmt=\"-o\", color=\"orange\", markersize=10\n",
    "        )\n",
    "        if df_sim is not None:\n",
    "            df_sim.loc[:, \"rt_bin\"] = pd.qcut(df_sim[\"rt\"], quantiles, labels=False)\n",
    "            d = df_sim.groupby([\"rt_bin\"]).mean().reset_index()\n",
    "            ax.errorbar(\n",
    "                d.loc[:, \"rt\"], d.loc[:, \"correct\"], fmt=\"x\", color=\"k\", markersize=6\n",
    "            )\n",
    "        if xlim:\n",
    "            ax.set_xlim(xlim)\n",
    "        ax.set_ylim(0, 1.25)\n",
    "        ax.set_title(\"Conditional accuracy\")\n",
    "        ax.set_xlabel(\"RT (quantiles)\")\n",
    "        ax.set_ylabel(\"P(correct)\")\n",
    "        plt_nr += 1\n",
    "\n",
    "        # rt distributions response 1 vs 0:\n",
    "        ax = fig.add_subplot(nr_subjects, 4, plt_nr)\n",
    "        if np.isnan(df[\"rt\"]).sum() > 0:\n",
    "            # some initial computations\n",
    "            bar_width = 1\n",
    "            fraction_yes = df[\"response\"].mean()\n",
    "            fraction_yes_sim = df_sim[\"response\"].mean()\n",
    "            no_height = (1 - fraction_yes) / bar_width\n",
    "            no_height_sim = (1 - fraction_yes_sim) / bar_width\n",
    "\n",
    "            hist, edges = np.histogram(\n",
    "                df.loc[:, \"rt_resp\"],\n",
    "                bins=bins,\n",
    "                density=True,\n",
    "            )\n",
    "            hist = hist * fraction_yes\n",
    "            hist_sim, edges_sim = np.histogram(\n",
    "                df_sim.loc[:, \"rt_resp\"],\n",
    "                bins=bins,\n",
    "                density=True,\n",
    "            )\n",
    "            hist_sim = hist_sim * fraction_yes_sim\n",
    "\n",
    "            # Add histogram from go choices\n",
    "            # ground truth\n",
    "            ax.bar(\n",
    "                edges[:-1],\n",
    "                hist,\n",
    "                width=np.diff(edges)[0],\n",
    "                align=\"edge\",\n",
    "                color=\"magenta\",\n",
    "                alpha=0.5,\n",
    "                linewidth=0,\n",
    "            )\n",
    "            # simulations\n",
    "            ax.step(edges_sim[:-1] + np.diff(edges)[0], hist_sim, color=\"black\", lw=1)\n",
    "\n",
    "            # Add bar for the no-go choices (on the negative rt scale)\n",
    "            # This just illustrates the probability of no-go choices\n",
    "\n",
    "            # ground truth\n",
    "            ax.bar(\n",
    "                x=-1.5,\n",
    "                height=no_height,\n",
    "                width=bar_width,\n",
    "                alpha=0.5,\n",
    "                color=\"cyan\",\n",
    "                align=\"center\",\n",
    "            )\n",
    "\n",
    "            # simulations\n",
    "            ax.hlines(\n",
    "                y=no_height_sim,\n",
    "                xmin=-2,\n",
    "                xmax=-1,\n",
    "                lw=0.5,\n",
    "                colors=\"black\",\n",
    "            )\n",
    "            ax.vlines(x=-2, ymin=0, ymax=no_height_sim, lw=0.5, colors=\"black\")\n",
    "            ax.vlines(x=-1, ymin=0, ymax=no_height_sim, lw=0.5, colors=\"black\")\n",
    "        else:\n",
    "            N, bins, patches = ax.hist(\n",
    "                df.loc[:, \"rt_resp\"],\n",
    "                bins=bins,\n",
    "                density=True,\n",
    "                color=\"magenta\",\n",
    "                alpha=0.5,\n",
    "            )\n",
    "            for bin_size, bin, patch in zip(N, bins, patches):\n",
    "                if bin < 0:\n",
    "                    plt.setp(patch, \"facecolor\", \"cyan\")\n",
    "            ax.hist(\n",
    "                df_sim.loc[:, \"rt_resp\"],\n",
    "                bins=bins,\n",
    "                density=True,\n",
    "                histtype=\"step\",\n",
    "                color=\"k\",\n",
    "                alpha=1,\n",
    "                label=None,\n",
    "            )\n",
    "\n",
    "        ax.set_title(\n",
    "            \"P(bias)={}\".format(\n",
    "                round(df.loc[:, \"response\"].mean(), 3),\n",
    "            )\n",
    "        )\n",
    "        ax.set_xlabel(\"RT (s)\")\n",
    "        ax.set_ylabel(\"Trials (prob. dens.)\")\n",
    "        plt_nr += 1\n",
    "\n",
    "        # condition response plots:\n",
    "        ax = fig.add_subplot(nr_subjects, 4, plt_nr)\n",
    "        df.loc[:, \"rt_bin\"] = pd.qcut(df[\"rt\"], quantiles, labels=False)\n",
    "        d = df.groupby([\"rt_bin\"]).mean().reset_index()\n",
    "        ax.errorbar(\n",
    "            d.loc[:, \"rt\"],\n",
    "            d.loc[:, \"response\"],\n",
    "            fmt=\"-o\",\n",
    "            color=\"orange\",\n",
    "            markersize=10,\n",
    "        )\n",
    "        if df_sim is not None:\n",
    "            df_sim.loc[:, \"rt_bin\"] = pd.qcut(df_sim[\"rt\"], quantiles, labels=False)\n",
    "            d = df_sim.groupby([\"rt_bin\"]).mean().reset_index()\n",
    "            ax.errorbar(\n",
    "                d.loc[:, \"rt\"], d.loc[:, \"response\"], fmt=\"x\", color=\"k\", markersize=6\n",
    "            )\n",
    "        if xlim:\n",
    "            ax.set_xlim(xlim)\n",
    "        ax.set_ylim(0, 1.25)\n",
    "        ax.set_title(\"Conditional response\")\n",
    "        ax.set_xlabel(\"RT (quantiles)\")\n",
    "        ax.set_ylabel(\"P(bias)\")\n",
    "        plt_nr += 1\n",
    "\n",
    "    sns.despine(offset=3, trim=True)\n",
    "    plt.tight_layout()\n",
    "\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's simulate our own data, so we know what the fitting procedure should converge on:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# settings\n",
    "go_nogo = True  # should we put all RTs for one choice alternative to NaN (go-no data)?\n",
    "n_subjects = 4\n",
    "trials_per_level = 10000\n",
    "\n",
    "# parameters:\n",
    "params0 = {\n",
    "    \"cond\": 0,\n",
    "    \"v\": 0.5,\n",
    "    \"a\": 2.0,\n",
    "    \"t\": 0.3,\n",
    "    \"z\": 0.5,\n",
    "    \"dc\": -0.2,\n",
    "    \"sz\": 0,\n",
    "    \"st\": 0,\n",
    "    \"sv\": 0,\n",
    "}\n",
    "params1 = {\n",
    "    \"cond\": 1,\n",
    "    \"v\": 0.5,\n",
    "    \"a\": 2.0,\n",
    "    \"t\": 0.3,\n",
    "    \"z\": 0.5,\n",
    "    \"dc\": 0.2,\n",
    "    \"sz\": 0,\n",
    "    \"st\": 0,\n",
    "    \"sv\": 0,\n",
    "}\n",
    "\n",
    "# simulate:\n",
    "dfs = []\n",
    "for i in range(n_subjects):\n",
    "    df0 = simulate_data(\n",
    "        z=params0[\"z\"],\n",
    "        a=params0[\"a\"],\n",
    "        v=params0[\"v\"],\n",
    "        dc=params0[\"dc\"],\n",
    "        t=params0[\"t\"],\n",
    "        sv=params0[\"sv\"],\n",
    "        st=params0[\"st\"],\n",
    "        sz=params0[\"sz\"],\n",
    "        condition=params0[\"cond\"],\n",
    "        nr_trials1=trials_per_level,\n",
    "        nr_trials2=trials_per_level,\n",
    "    )\n",
    "    df1 = simulate_data(\n",
    "        z=params1[\"z\"],\n",
    "        a=params1[\"a\"],\n",
    "        v=params1[\"v\"],\n",
    "        dc=params1[\"dc\"],\n",
    "        t=params1[\"t\"],\n",
    "        sv=params1[\"sv\"],\n",
    "        st=params1[\"st\"],\n",
    "        sz=params1[\"sz\"],\n",
    "        condition=params1[\"cond\"],\n",
    "        nr_trials1=trials_per_level,\n",
    "        nr_trials2=trials_per_level,\n",
    "    )\n",
    "    df = pd.concat((df0, df1))\n",
    "    df[\"subj_idx\"] = i\n",
    "    dfs.append(df)\n",
    "\n",
    "# combine in one dataframe:\n",
    "df_emp = pd.concat(dfs)\n",
    "if go_nogo:\n",
    "    df_emp.loc[df_emp[\"response\"] == 0, \"rt\"] = np.NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "  </tbody>\n",
       "</table>\n",
       "<p>160000 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         rt  response  subj_idx  condition  correct  stimulus\n",
       "0     0.880         1         0          0        1         1\n",
       "1       NaN         0         0          0        0         1\n",
       "2     1.499         1         0          0        1         1\n",
       "3       NaN         0         0          0        0         1\n",
       "4       NaN         0         0          0        0         1\n",
       "...     ...       ...       ...        ...      ...       ...\n",
       "9995  0.829         1         3          1        0         0\n",
       "9996  0.938         1         3          1        0         0\n",
       "9997  1.674         1         3          1        0         0\n",
       "9998    NaN         0         3          1        1         0\n",
       "9999    NaN         0         3          1        1         0\n",
       "\n",
       "[160000 rows x 6 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_emp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fit using the g-quare method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fit chi-square:\n",
    "quantiles = [0.1, 0.3, 0.5, 0.7, 0.9]\n",
    "params_fitted = pd.concat(\n",
    "    Parallel(n_jobs=n_subjects)(\n",
    "        delayed(fit_subject)(data[1], quantiles) for data in df_emp.groupby(\"subj_idx\")\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       a(0)      a(1)      v(0)      v(1)      t(0)      t(1)      z(0)  \\\n",
      "0  1.957684  1.997512  0.506885  0.503210  0.291217  0.304618  0.476925   \n",
      "1  1.992596  2.009814  0.495720  0.514267  0.286401  0.271875  0.481426   \n",
      "2  1.971131  1.996191  0.522817  0.495448  0.270259  0.283106  0.451006   \n",
      "3  1.999619  1.972885  0.501150  0.493823  0.309258  0.298655  0.512594   \n",
      "\n",
      "       z(1)     dc(0)     dc(1)  \n",
      "0  0.503880 -0.157141  0.197714  \n",
      "1  0.470882 -0.158436  0.259854  \n",
      "2  0.478944 -0.096833  0.231788  \n",
      "3  0.489152 -0.223152  0.236227  \n"
     ]
    }
   ],
   "source": [
    "params_fitted.drop(\n",
    "    [\"bic\", \"likelihood\", \"penalty\", \"z_trans(0)\", \"z_trans(1)\"], axis=1, inplace=True\n",
    ")\n",
    "print(params_fitted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# simulate data based on fitted params:\n",
    "dfs = []\n",
    "for i in range(n_subjects):\n",
    "    df0 = simulate_data(\n",
    "        a=params_fitted.loc[i, \"a(0)\"],\n",
    "        v=params_fitted.loc[i, \"v(0)\"],\n",
    "        t=params_fitted.loc[i, \"t(0)\"],\n",
    "        z=params_fitted.loc[i, \"z(0)\"],\n",
    "        dc=params_fitted.loc[i, \"dc(0)\"],\n",
    "        condition=0,\n",
    "        nr_trials1=trials_per_level,\n",
    "        nr_trials2=trials_per_level,\n",
    "    )\n",
    "    df1 = simulate_data(\n",
    "        a=params_fitted.loc[i, \"a(1)\"],\n",
    "        v=params_fitted.loc[i, \"v(1)\"],\n",
    "        t=params_fitted.loc[i, \"t(1)\"],\n",
    "        z=params_fitted.loc[i, \"z(1)\"],\n",
    "        dc=params_fitted.loc[i, \"dc(1)\"],\n",
    "        condition=1,\n",
    "        nr_trials1=trials_per_level,\n",
    "        nr_trials2=trials_per_level,\n",
    "    )\n",
    "    df = pd.concat((df0, df1))\n",
    "    df[\"subj_idx\"] = i\n",
    "    dfs.append(df)\n",
    "df_sim = pd.concat(dfs)\n",
    "if go_nogo:\n",
    "    df_sim.loc[df_sim[\"response\"] == 0, \"rt\"] = np.NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rt</th>\n",
       "      <th>response</th>\n",
       "      <th>subj_idx</th>\n",
       "      <th>condition</th>\n",
       "      <th>correct</th>\n",
       "      <th>stimulus</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.668217</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.870217</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.025217</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.914217</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.033217</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>0.676655</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>0.853655</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>160000 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            rt  response  subj_idx  condition  correct  stimulus\n",
       "0     1.668217         1         0          0        1         1\n",
       "1     1.870217         1         0          0        1         1\n",
       "2     3.025217         1         0          0        1         1\n",
       "3     0.914217         1         0          0        1         1\n",
       "4     1.033217         1         0          0        1         1\n",
       "...        ...       ...       ...        ...      ...       ...\n",
       "9995       NaN         0         3          1        1         0\n",
       "9996       NaN         0         3          1        1         0\n",
       "9997       NaN         0         3          1        1         0\n",
       "9998  0.676655         1         3          1        0         0\n",
       "9999  0.853655         1         3          1        0         0\n",
       "\n",
       "[160000 rows x 6 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sim"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot true vs recovered parameters:\n",
    "x = np.arange(5) * 2\n",
    "y0 = np.array([params0[\"a\"], params0[\"v\"], params0[\"t\"], params0[\"z\"], params0[\"dc\"]])\n",
    "y1 = np.array([params1[\"a\"], params1[\"v\"], params1[\"t\"], params1[\"z\"], params1[\"dc\"]])\n",
    "fig = plt.figure(figsize=(5, 2))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.scatter(x, y0, marker=\"o\", s=100, color=\"orange\", label=\"True value\")\n",
    "ax.scatter(\n",
    "    x + 1,\n",
    "    y1,\n",
    "    marker=\"o\",\n",
    "    s=100,\n",
    "    color=\"orange\",\n",
    ")\n",
    "sns.stripplot(\n",
    "    data=params_fitted,\n",
    "    jitter=False,\n",
    "    size=2,\n",
    "    edgecolor=\"black\",\n",
    "    linewidth=0.25,\n",
    "    alpha=1,\n",
    "    palette=[\"black\", \"black\"],\n",
    "    ax=ax,\n",
    ")\n",
    "plt.ylabel(\"Param value\")\n",
    "plt.legend()\n",
    "sns.despine(\n",
    "    offset=5,\n",
    "    trim=True,\n",
    ")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CONDITION 0\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CONDITION 1\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot data with model fit on top:\n",
    "for c in np.unique(df_emp[\"condition\"]):\n",
    "    print(\"CONDITION {}\".format(c))\n",
    "    summary_plot(\n",
    "        df_group=df_emp.loc[(df_emp[\"condition\"] == c), :],\n",
    "        df_sim_group=df_sim.loc[(df_emp[\"condition\"] == c), :],\n",
    "    )\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
